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EN
Artificial neural networks (ANN) are a powerful tool in the decision-making process, especially in solving the complex problems with a large number of input data. The possibility to predict the work-related injuries in the underground coal mines, based on application of the neural networks, is analyzed in this work. the input data for the network were obtained based on a survey of 1300 respondents. After analyzing the input data influence on the network output, 14 most influential inputs were selected, with help of which the network correctly predicted whether the worker would suffer the work-related injury or not, with 80% precision. The two models were developed, based on the multilayer perceptron (MLP) and radial basis function (RBF) networks. The two models' results were compared to each other. The sensitivity analysis was used to select the most influential parameters, like mine, age of miners, as well as their work experience. The parameters were further analyzed by use of the descriptive statistics. The selected parameters are direct indicators of problems that can cause injuries. The obtained results point to the fact that the work-related injuries can be successfully predicted by application of the artificial neural networks. The proposed models' importance is reflected in the clear indicators for enforcing the stricter occupational safety and organizational measures in order to reduce the number of work-related injuries in underground mines.
EN
The mining industry in Serbia has an important place in the country's economic development. Bearing in mind that the number of injuries that occur in the mining industry is unacceptably high, occupational safety and health is a challenge that existing and future mines will have to deal with. Studying injuries in mining, it was noticed that injuries requiring an absence from work for more than three days (especially fatal ones) are diametrically different in relation to the cause and manner of events related to injuries for which an absence from work is not necessary. In this research, authors focused on injuries that were characterized as ones requiring an absence from work. The statistical analysis of work-related injuries in mining is presented, as well as analysis of the direct causes of injuries, which are described as unsafe conduct of employees, unsafe conduct of company's management and/or unsafe working environment. In relation to classification of causes of injuries, a recommendation on what needs to be changed in order to remedy this situation in Serbia is given.
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